Explainable Graph Spectral Clustering For Text Embeddings
By: Mieczysław A. Kłopotek , Sławomir T. Wierzchoń , Bartłomiej Starosta and more
Potential Business Impact:
Helps computers understand text better with new methods.
In a previous paper, we proposed an introduction to the explainability of Graph Spectral Clustering results for textual documents, given that document similarity is computed as cosine similarity in term vector space. In this paper, we generalize this idea by considering other embeddings of documents, in particular, based on the GloVe embedding idea.
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